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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Ethical dilemmas in nursing are of utmost importance, as they often arise from the tension between adhering to core ethical principles and the practical realities of healthcare delivery. These dilemmas require nurses to navigate complex situations where competing ethical considerations pull them in different directions.
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Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
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相关实验视频

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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在儿科中可解释的人工智能:未来的挑战

Ahmed M Salih1,2,3,4, Gloria Menegaz5, Thillagavathie Pillay6

  • 1Department of Population Health Sciences University of Leicester Leicester UK.

Health science reports
|December 13, 2024
PubMed
概括
此摘要是机器生成的。

可解释的人工智能 (XAI) 在机器学习中提供了透明度,但在儿科中需要谨慎使用. 必须通过涉及儿科医生和领域知识来解决像通用性和可信度这样的挑战,以确保安全的采用.

关键词:
挑战 挑战 挑战 挑战 挑战可解释的人工智能解释解释解释的意思儿科 儿科医生 儿科

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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 儿科 儿科 儿科

背景情况:

  • 可解释的人工智能 (XAI) 旨在提高机器学习模型的透明度和人类对AI决策的理解.
  • 为了更好地理解人类,XAI简化了复杂的模型.
  • 由于潜在的不良结果,目前的XAI开发需要在儿科等敏感领域谨慎应用.

研究的目的:

  • 讨论在儿科中实施和解释XAI方法时的担忧和挑战.
  • 提高对阻碍XAI在儿科护理中的采用关键问题的认识.

主要方法:

  • 进行了全面的文献审查.
  • 审查的重点是探索与采用XAI在儿科领域相关的挑战.

主要成果:

  • 在儿科中实施XAI面临着重大挑战,包括一般化,可信度,因果关系和干预等问题.
  • 评估XAI方法是一个关键的障碍.

结论:

  • 儿科是一个高风险领域,人工智能误解可能会产生严重后果.
  • 在儿科中采用XAI需要仔细评估,儿科医生参与,并整合领域知识来弥合现有的差距.